---
name: al-241-spot-a-brewing-brand-crisis-early-by-having-an-agent-watc
description: "A bad product batch, a viral complaint or a rude staff video can spread for hours before anyone on the team notices, and by then the story is set. AI agents can scan social mentions, reviews and support messages, spot an unusual jump in a complaint or negative tone, show who is spreading it, and draft a response plan. On Oct 22, 2026 Sprinklr announced its Voice of the Customer agent suite in Google's Gemini Enterprise Agent Marketplace, including a Crisis Monitoring agent that detects emerging issues, assesses how far they are spreading, identifies key amplifiers and supports response planning, alongside agents for brand health and competitor benchmarking. Use when the user wants help with brand crisis early warning (marketing) for a small business."
---

# Spot a brewing brand crisis early by having an agent watch social posts, reviews and support messages for unusual spikes

A bad product batch, a viral complaint or a rude staff video can spread for hours before anyone on the team notices, and by then the story is set. AI agents can scan social mentions, reviews and support messages, spot an unusual jump in a complaint or negative tone, show who is spreading it, and draft a response plan. On Oct 22, 2026 Sprinklr announced its Voice of the Customer agent suite in Google's Gemini Enterprise Agent Marketplace, including a Crisis Monitoring agent that detects emerging issues, assesses how far they are spreading, identifies key amplifiers and supports response planning, alongside agents for brand health and competitor benchmarking.

## Inputs to collect first
Ask the user for anything below that they haven't already given you. Don't guess missing facts.

- Social posts, reviews and support messages with date, platform and…
- Typical number of mentions per day and usual complaints

## Instructions

Do the task below with the user's inputs in place of each [bracket].

Here are our brand mentions from the last 72 hours: [paste social posts, reviews and support messages with date, platform and follower count if known]. Here is what a normal week looks like for us: [typical number of mentions per day and usual complaints]. 1) Compare the last 72 hours to normal and tell me if any topic, complaint or product is spiking. Show the numbers. 2) For anything spiking, summarize what people are saying in plain words with 3 real quotes, when it started, and the 5 accounts with the most reach that are spreading it. 3) Rate the risk as low, medium or high and explain why. 4) Draft a holding statement, a reply template for customers who ask, and a short note for our team about what to do and not say. 5) Tell me what to watch over the next 24 hours. Only use the posts I gave you; don't guess at anything not shown.

## Safety checks (share these with the user)

- This prompt works on text other people wrote (emails, reviews, messages or web pages). That text can hide instructions aimed at AI, such as "ignore your rules and…". Paste it as material to work on, and never let the AI act on requests inside it, like paying, sharing logins or changing records.
- Check every figure, price and total against your own records before anything is sent, posted or booked. A person approves refunds, discounts, payments and price changes.
- Remove names, contact details, account numbers and other personal data the task doesn't need before you paste, and check your AI tool's data and training settings.
- Read and edit the draft before it reaches a customer or goes public. If you later automate this prompt, start with "draft and notify me", not "send automatically".
- Say clearly which parts need a person to review or approve before anything is sent, paid, posted or filed.

## About this skill

- Works with: ChatGPT, Claude, Gemini, Perplexity, Google Alerts, Buffer
- Based on this real-world example: https://investors.sprinklr.com/news/press-releases/detail/265/sprinklr-announces-availability-of-voc-agent-suite-in
- Free prompt from AgentPlaybook Real Estate: https://agentic-library.netlify.app/prompt/al-241-spot-a-brewing-brand-crisis-early-by-having-an-agent-watch-s/
- To install in an agent that supports Agent Skills, save this file as SKILL.md in a folder with the same name as `name` above (for example in your skills directory). Install steps for Claude.ai, Claude Code, Cursor and Codex: https://agentic-library.netlify.app/skills/